raster representation of data
grid/pixel size and resolution
raster data structures
advantages/disadvantages of raster and vector data models
data capture
rasterisation of vector data
raster to vector conversion

raster representation of data

Raster is a method for the storage, processing and display of spatial data. Each area is divided into rows and columns, which form a regular grid structure. Each cell must be rectangular in shape, but not necessarily square. Each cell within this matrix contains location co-ordinates as well as an attribute value. The spatial location of each cell is implicitly contained within the ordering of the matrix, unlike a vector structure which stores topology explicitly. Areas containing the same attribute value are recognised as such, however, raster structures cannot identify the boundaries of such areas as polygons.

Raster data is an abstraction of the real world where spatial data is expressed as a matrix of cells or pixels (see figure 9), with spatial position implicit in the ordering of the pixels. With the raster data model, spatial data is not continuous but divided into discrete units. This makes raster data particularly suitable for certain types of spatial operation, for example overlays or area calculations.

Raster structures may lead to increased storage in certain situations, since they store each cell in the matrix regardless of whether it is a feature or simply 'empty' space.

grid size and resolution

A pixel is the contraction of the words picture element. Commonly used in remote sensing to describe each unit in an image. In raster GIS the pixel equivalent is usually referred to as a cell element or grid cell. Pixel/cell refers to the smallest unit of information available in an image or raster map. This is the smallest element of a display device that can be independently assigned attributes such as colour.

Pixel size and number of rows and columns:
"The size of the pixel must be half of the smallest distance to be represented" Star and Estes (1990)

run-length encoding (figure 10)
This is a raster image compression technique. If a raster contains groups of cells with identical values, run length encoding can compress storage. Instead of storing each cell, each component stores a value and a count of cells with that value. If there is only one cell the storage doubles, but for three or more cells there is a reduction. The longer and more frequent the consecutive values are, the greater the compression that will be achieved. This technique is particularly useful for encoding monochrome images or binary images (Chrisman, 1997).

Figure 10. Run-length encoding

Data capture for raster datasets can include:

rasterisation of vector data

The process of converting vector data, which is a series of points, lines and polygons, into raster data, which is a series of cells each with a discrete value. This process is essentially easier than the reverse process, which is converting data from raster format to vector format.

raster to vector conversion
The process of converting an image made up of raster cells into one described by vector data. This may or may not involve the encoding of topology.